Hypohtesis Testing

Steps to hypothesis testing.

Hypothesis testing can be summarize in a six step procedure:

• Establish a null hypothesis as well as the alternative hypothesis.
• It is a one-tailed test of significance if the alternative hypothesis states the direction of no difference in the other hand if no direction or difference is given, it is a two-tailed test.
• Choose the statistical test on the basis of the assumption about the population distribution and measurement level.
• The form of the data can be a factor, in that case you will typically chose the test that has the greatest power efficiency or ability to reduce decision errors.
• Select the desired level of confidence.
• =0.5 is the most frequently used level, many others are also used.
• Compute the actual test value of the data.
• After the data is collected, use the formula for the appropriate significance test to obtain the calculated value. The computation results come from a software program.
• Obtain the critical test value, usually by referring to a table for the appropriate type of distribution.
• The critical value is the criterion that defines the region of rejection from the region of acceptance of the null hypothesis.
• Interpret the result by comparing the actual test value with the critical test value.
• For most test if the calculated value is larger than the critical value, we reject the null hypothesis and conclude that the alternative hypothesis is supported. If the critical value is larger, we conclude we have failed to reject the null.

 Hypothesis testing is crucial because it helps us to reason from evidence found in the sample  to conclusions. The virtues of this steps also allow us to to determine the accuracy of the hypotheses due to the fact that you have collected a sample of data.

Business Research Methods, Eleventh Edition. D. Cooper/P. Schindler